a dual cis-regulatory code links irf8 to constitutive and inducible...

A dual cis-regulatory code links IRF8to constitutive and inducible geneexpression in macrophages

Alessandra Mancino,1,3 Alberto Termanini,1,3 Iros Barozzi,1 Serena Ghisletti,1 Renato Ostuni,1

Elena Prosperini,1 Keiko Ozato,2 and Gioacchino Natoli1

1Department of Experimental Oncology, European Institute of Oncology (IEO), 20139 Milan, Italy; 2Laboratory of MolecularGrowth Regulation, Genomics of Differentiation Program, National Institute of Child Health and Human Development(NICHD), National Institutes of Health, Bethesda, Maryland 20892, USA

The transcription factor (TF) interferon regulatory factor 8 (IRF8) controls both developmental and inflammatorystimulus-inducible genes in macrophages, but the mechanisms underlying these two different functions arelargely unknown. One possibility is that these different roles are linked to the ability of IRF8 to bind alternativeDNA sequences. We found that IRF8 is recruited to distinct sets of DNA consensus sequences before and afterlipopolysaccharide (LPS) stimulation. In resting cells, IRF8 was mainly bound to composite sites together with themaster regulator of myeloid development PU.1. Basal IRF8–PU.1 binding maintained the expression of a broadpanel of genes essential for macrophage functions (such as microbial recognition and response to purines) andcontributed to basal expression of many LPS-inducible genes. After LPS stimulation, increased expression of IRF8,other IRFs, and AP-1 family TFs enabled IRF8 binding to thousands of additional regions containing low-affinitymultimerized IRF sites and composite IRF–AP-1 sites, which were not premarked by PU.1 and did not contributeto the basal IRF8 cistrome. While constitutively expressed IRF8-dependent genes contained only sites mediatingbasal IRF8/PU.1 recruitment, inducible IRF8-dependent genes contained variable combinations of constitutiveand inducible sites. Overall, these data show at the genome scale how the same TF can be linked to constitutiveand inducible gene regulation via distinct combinations of alternative DNA-binding sites.

[Keywords: IRF8; interferon; chromatin; epigenome; inflammation; macrophages; transcription]

Supplemental material is available for this article.

Received April 18, 2014; revised version accepted January 5, 2015.

Developmental specification of macrophages requires theactivity of a well-defined panel of transcription factors(TFs) (Rosenbauer and Tenen 2007) that act sequentiallyat specific stages, from the initial commitment of hema-topoietic stem cells (HSCs) to the myeloid fate and thento the terminally differentiated progeny (Lichtinger et al.2012). The ETS family TF PU.1 has a central role at allstages of myeloid development, starting from the transi-tion from HSCs to common myeloid progenitors (CMPs)(Rosenbauer and Tenen 2007). PU.1 is broadly expressedacross both themyeloid and lymphoid lineages. However,mainly due to post-translational control mechanisms, itreaches its highest intracellular concentration in macro-phages (Kueh et al. 2013). In these cells, it directlypromotes and maintains the accessibility of the genomiccis-regulatory information specifically available for con-

stitutive and stimulus-inducible transcriptional regula-tion in this cell type (Ghisletti et al. 2010; Heinz et al.2010; Barozzi et al. 2014). The generation of the macro-phage-specific repertoire of transcriptional enhancers alsorequires the ability of PU.1 to interact with partner TFsthat critically contribute to its recruitment to genomicbinding sites (Heinz et al. 2010; Barozzi et al. 2014;Gosselin and Glass 2014) and whose expression or activityis also dictated by cues coming from the tissue microen-vironment (Gosselin et al. 2014; Lavin et al. 2014).Among the PU.1 partners, a unique role is exerted by

interferon regulatory factor 8 (IRF8), a member of the IRFfamily (Tamura et al. 2008) whose expression is restrictedto the hematopoietic system. Within the myeloid com-partment, IRF8 is expressed from the GMP (granulocyte–

� 2015 Mancino et al. This article is distributed exclusively by ColdSpring Harbor Laboratory Press for the first six months after the full-issuepublication date (see http://genesdev.cshlp.org/site/misc/terms.xhtml).After six months, it is available under a Creative Commons License(Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

3These authors contributed equally to this work.Corresponding author: [email protected] published online ahead of print. Article and publication date areonline at http://www.genesdev.org/cgi/doi/10.1101/gad.257592.114.

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macrophage progenitor) stage onward and is exquisitelyselective for the monocyte–macrophage branch (Tamuraet al. 2000). In keeping with this expression profile, Irf8gene deletion in mice results in a myeloproliferativesyndrome with a massive accumulation of granulocytesand reduced monocyte–macrophages, thus suggestingthat IRF8 is required for GMP differentiation into mono-cytes and that, in its absence, myeloid progenitors gen-erate granulocytes at a higher rate. Moreover, IRF8 is alsorequired for the development of CD8a+ and plasmacytoiddendritic cells (pDCs) (Schiavoni et al. 2002; Tsujimuraet al. 2003). Consistent with these phenotypes, IRF8 loss-of-function mutations in humans (Hambleton et al. 2011)are also associated with major defects of the monocyteand dendritic cell compartment.In contrast with a more common dichotomy between

TFs involved in development and TFs involved in envi-ronmental responses, IRF8 is required for not only mac-rophage differentiation but also the stimulus-inducibleexpression of some critical immune response genes suchas Il12p40 (which controls T-lymphocyte polarization)and Ifnb1. The autocrine and paracrine activities oflipopolysaccharide (LPS)-induced IFNb greatly contributeto the transcriptional response to LPS, since a largefraction of the genes activated by LPS (including manyantimicrobial genes) are in fact secondary genes inducedby IFNb (Thomas et al. 2006). Such a functional dualityalso explains the immunodeficiency syndrome of Irf8mutant mice and humans and specifically their highsusceptibility to intracellular macrophage pathogens(Turcotte et al. 2005; Marquis et al. 2009; Hambletonet al. 2011). How these different IRF8 activities in de-velopment and inflammatory responses are hardwiredinto the genome remains to be understood.Because of structural divergences in their IRF domain

(Escalante et al. 2002), IRF8 and its closest paralog, IRF4,are virtually unable to bind DNA with high affinityunless associated with DNA-binding partners such asPU.1, other IRFs, and JUN/AP-1 family proteins (Escalanteet al. 2002; Tamura et al. 2005; Glasmacher et al. 2012;Li et al. 2012; Tussiwand et al. 2012). A C-terminalregion of IRF8 named IAD (IRF association domain) isspecifically involved in making protein–protein contactswith binding partners. Consistently, a point mutation ata single amino acid in the IRF8 IAD (Arg294>Cys) in theBxh2 mouse causes a phenotype that is almost indistin-guishable from the total loss of IRF8 (Turcotte et al. 2005),the only exception being the conservation of pDCs inBxh2 mice (Tailor et al. 2008). A direct implication ofIRF4/8’s dependence on partner TFs for high-affinityDNA binding is their ability to recognize DNA sequencesdistinct from the canonical IRF-binding site (known asISRE [interferon-stimulated response element]), includingthe ETS/IRF composite elements (EICEs) in associationwith PU.1 (Taniguchi et al. 2001) and the AP-1/IRF com-posite elements (AICEs) in association with ATF and JUN/AP-1 family proteins (Glasmacher et al. 2012; Li et al. 2012).While some of the biological roles of IRF8 duringmyeloid

development are well established, the molecular bases ofits dual role during lineage specification and acute envi-

ronmental responses are unclear but are likely linked to itsunique DNA-binding properties. To specifically addressthis question, we investigated the genomic distribution ofIRF8 and its role in controlling the chromatin landscapeand the gene expression programs of mouse macrophagesbefore and after LPS and type I IFN stimulation. Our dataindicate that the genomic distribution of IRF8 in macro-phages has two distinct components; namely, a constitutivecomponent dependent on the interaction of PU.1–IRF8complexes with EICEs and an inducible component thatis restricted tomultimerized IRF sites and composite IRF/AP-1 sites and that possibly depends on the LPS-inducedincreased expression of IRF8, IRF1, and AP-1 family TFs.Constitutive IRF8–PU.1 binding maintained the basalexpression of a large panel of macrophage genes, includ-ing IFNb-inducible genes. In turn, upon LPS stimulation,IRF8 not only was required for efficient Ifnb1 geneinduction but also collaborated with IFNb-activatedSTAT1 to promote chromatin and gene expressionchanges in response to type I IFN. Overall, these dataprovide the mechanistic basis underlying the functionalduality of IRF8 in both macrophage development andacute antimicrobial responses. More generally, they pro-vide detailed and mechanistic insight into how a singleTF can be coupled to multiple gene expression programs.

Results

Constitutive and inducible IRF8 recruitmentto distinct DNA-binding sites

We first analyzed the genomic distribution of IRF8 inuntreated and LPS-treated mouse bone marrow-derivedmacrophages using chromatin immunoprecipitation(ChIP) coupled to high-throughput sequencing (ChIP-seq). IRF8 was constitutively bound to thousands of sitesin untreated macrophages (9056 sites using a MACSP-value of 1 3 10�10) (Fig. 1A). Although ChIP-seq dataobtained with different antibodies may not be directlycomparable, the genomic distribution of IRF8 appeared tobe much more restricted than that of PU.1, since, usingthe same parameters for peak calling, we could detect60,931 PU.1 peaks. This difference was not accounted forby a different efficiency of the PU.1 and IRF8 ChIPs, sincethe signal to noise ratio (measured as the ratio betweenthe number of sequencing reads contained in peaks[signal] and those outside of peaks [noise]) was similar.LPS stimulation increased the number of IRF8 peaks andcaused a doubling in their number after a 4-h treatment(Fig. 1A). These data indicate that two distinct compo-nents account for the IRF8 genomic distribution (Fig. 1B);namely, a constitutive component (n = 6448) and aninducible component (n = 7509). An additional minorcomponent was represented by genomic regions fromwhich IRF8 was released after LPS stimulation (repressedpeaks, n = 1120) (Supplemental Table 1). Both constitu-tive and inducible IRF8 peaks in general overlapped withPU.1 peaks (Fig. 1A). However, most inducible IRF8 peaksoccurred at genomic regions that, in unstimulated mac-rophages, were not prebound by PU.1, as indicated by

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both the heat map in Figure 1B and an analysis of thedistance between the summit of PU.1 and IRF8 ChIP-seqpeaks (Fig. 1C): Using the PU.1 peaks detected in unstim-ulated macrophages as viewpoints, 75% of constitutiveIRF8 peaks (Fig. 1C, top panel) but only <20% of theinducible ones (Fig. 1C, bottom panel) were detectedwithin a distance of 32 nucleotides (nt). Overall, thesedata suggest that cobinding of IRF8 and PU.1 in unstimu-lated macrophages is a most common event. However,LPS-induced new binding events occurred mainly in

regions that were not constitutively bound by PU.1.These data suggest a fundamentally different mechanismof IRF8 recruitment to constitutively and induciblybound sites. A representative genomic region showingboth constitutive and inducible IRF8 peaks and theirrelationship with PU.1 is displayed in Figure 1D.The two distinct types of IRF8 peaks carried functional

specificities, as shown by the overrepresentation of distinctontology terms associated with the neighboring genes.GREAT (genomic regions enrichment of annotations tool)

Figure 1. Constitutive and inducible IRF8 binding in macrophages. (A) Number of IRF8 peaks identified by ChIP-seq in untreated (UT)and LPS-treated macrophages (MACS P < 1 3 10�10). (B) Heat map of constitutive, LPS-inducible, and LPS-repressed IRF8 peaks. Pu.1ChIP-seq data at the same time points are also shown. The box plots at the bottom show the intensity of ChIP-seq signals in thedifferent groups. (C) Cumulative distribution of the distances between constitutive IRF8 peaks in untreated macrophages and LPS-inducible (2-h) IRF8 peaks relative to PU.1 peaks in untreated macrophages. (D) Representative ChIP-seq snapshot showing constitutiveand LPS-inducible (arrows) IRF8 peaks. (E) Selected ontology categories enriched in the two sets of IRF8-bound genomic regionsaccording to GREAT. (F) IRF8 protein levels in LPS-treated macrophages. Tubulin was used as loading control. Bands were quantifiedusing the Li-Cor system.

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computes the enrichment of ontology terms in a set ofgenomic regions extracted from sequencing data (McLeanet al. 2010). When considering the genomic regions asso-ciated with the constitutive IRF8 peaks, GREAT retrieved,among the others, ontology terms related to purinergicreceptor signaling, while the inducible IRF8 peaks werespecifically associated with IL-12 and IL-23 signaling (Fig.1E; Supplemental Table 2). These results are in keepingwith the role of IRF8 in controlling the expression of thecorresponding genes (see below).Consistent with previous reports (Xu et al. 2012), the

IRF8 protein was transiently induced with a peak (3.83increase) at 4 h after LPS stimulation (Fig. 1F). Therefore,the overall increase in genomic IRF8 occupancy after LPStreatment may be driven by both its increased expression(see below) and LPS-mediated induction of other IRF8-binding partners (including AP-1 and ATF family TFs)(Glasmacher et al. 2012; Li et al. 2012) as well as other IRFproteins (such as IRF1).To contribute to our understanding of this issue and

also determine how the different DNA-binding domainsof IRF8 and IRF1 impact their genomic distribution, weanalyzed the genomic occupancy of IRF1 in unstimulatedmacrophages and after LPS stimulation, which greatlyincreases IRF1 expression. IRF1 binding was limited toa few thousand sites in unstimulated macrophages butincreased about three times in response to LPS stimula-tion (Fig. 2A; Supplemental Table 3), which is consistentwith its increased expression. Compared with IRF8, theoverlap with PU.1 was more limited (Fig. 2A), and thedistance from PU.1 peaks was higher (Fig. 2B). Overall,the genomic distribution of IRF1 was largely distinctfrom that of IRF8 in unstimulated macrophages (withonly 17% of IRF8 peaks overlapping IRF1 peaks) (Fig. 2C),but the overlap strongly increased in response to stimu-lation (40.2% at 2 h and 43% at 4 h). These data suggestthat the DNA-binding sites (and the cooperating TFs) thatcontrol basal IRF8 and IRF1 recruitment were largelydistinct. However, in response to stimulation, the twofactors bound to a large number of shared regions,suggesting the usage of similar binding sites. A de novomotif discovery analysis showed that IRF1 unique sitesand those regions in which IRF1 and IRF8 overlapped at4 h after LPS treatment were associated with a very similarmultimerized IRF-binding site, while the IRF8 uniquepeaks were associated with a composite ETS/IRF-bindingsite containing at the 59 end the 59-GGAA-39 moietycharacteristic of the core binding site of all ETS familyTFs and at the 39 end the 59-GAAA-39 that represents thecore IRF-binding site (Fig. 2D). A representative snapshotwith some differential peaks highlighted is shown inFigure 2E. Therefore, a specific type of ETS/IRF sitedefines a subgroup of unique IRF8-binding events thatare not shared with other IRF family TFs.

A limited number of DNA-binding sites predict basalvs. inducible IRF8 binding

When considering the relationship between IRF8 andPU.1, a clear difference between constitutive and in-

ducible peaks became apparent. First, a higher fractionof inducible than constitutive IRF8 peaks was not asso-ciated with PU.1 at all (Fig. 1A, light gray). Second, whenconsidering the inducible IRF8 peaks, themedian numberof tags of the overlapping PU.1 peaks was much lowerthan that of PU.1 peaks coinciding with constitutive IRF8(2.2-fold; P < 2.23 10�16Wilcoxon rank sum test) (Fig. 1B,box plots). Third, inducible IRF8 peaks often occurred atgenomic regions that were not prebound by PU.1 inunstimulatedmacrophages (Fig. 1C, bottom panel). Thesedata suggest that the mode of binding of IRF8 at consti-tutive and inducible peaks may differ. Consistently, a denovo motif discovery analysis revealed that while con-stitutive peaks were mainly associated with PU.1/IRF8composite sites (PWM1) (Fig. 3A, left panel), the inducibleones showed an overrepresentation of a multimerized 59-GAAA-39 motif that corresponds to a canonical IRF half-site (PWM2) (Fig. 3A, left panel; Taniguchi et al. 2001).Consistently, overexpression of IRF8 by retroviral trans-duction of macrophages promoted its recruitment togenomic regions that recruited IRF8 only in response toLPS stimulation and contained multimerized IRF sites(Supplemental Fig. 1A). Using an in vitro pull-down assaywith an immobilized biotinylated oligonucleotide con-taining a multimerized IRF site, we could retrieve IRF8,albeit with a comparatively lower efficiency than ob-served with a composite PU.1/IRF8 probe (SupplementalFig. 1B). LPS-inducible IRF8 recruitment via multimerizedISRE-like sites to regions of the genome that are PU.1-negative before stimulation (Fig. 1C) suggests that PU.1recruitment in these cases may be mediated by protein–protein interactions with IRF8 rather than direct rec-ognition of cognate DNA-binding sites, which wouldalso explain its lower signal intensity at these regions(Fig. 1B).To mechanistically understand the impact of different

DNA-binding sites on basal versus inducible IRF8 bind-ing, we first measured howmany peaks in the two groupscontained either of these two DNA-binding consensussites. To increase the precision of this analysis, we trans-formed the PWMs into two DNA strings (DS1 and DS2)(Fig. 3A, middle panel) and determined the fraction ofpeaks with a perfect match. The two DSs showed a veryskewed association with the two groups of peaks, butsince they were detected in only a fraction of them, theywere clearly not sufficient to mechanistically explaindifferential IRF8 recruitment. Therefore, we identifiedthree additional (‘‘secondary’’) PWMs (and the corre-sponding DSs) in all of those peaks without a match(Fig. 3A, right panel). PWM3/DS3 correspond to a dimericIRF site, PWM4/DS4 correspond to a composite site inwhich the position of the ETS and IRF sites are invertedrelative to PWM1, and PWM5/DS5 correspond to an IRF–AP-1 site (Glasmacher et al. 2012; Li et al. 2012). A sixthDS (DS6) was generated from a relatively degeneratedmatrix that has no obvious match to annotated TF DNA-binding sites.Next, we set out to determine to what extent these

PWMs and DSs predict constitutive versus inducibleIRF8 binding at a genome scale. To this aim, we used






support vector machines (SVMs) (Cortes and Vapnik1995) coupled with a feature selection procedure (Guyonand Elisseeff 2003) that would allow us to determinewhich DNA-binding sites have the highest predictivepower (Supplemental Material) (Fig. 3B). Given a set ofexamples (namely, a training set), an SVM learningalgorithm builds a model that can then be used to classifynew data (namely, a test set) (Fig. 3B). We trained the SVMusing 50% of the constitutive and inducible IRF8 sitesand then used the trained SVM to predict constitutiveversus inducible IRF8 binding to the remaining 50%.When the SVMwas fed with only the five PWMs (SVM1),it reached a remarkable prediction accuracy between71% and 76% (Fig. 3C); the addition of the six DSs(SVM2) increased the SVM accuracy to a minimum of75% and a maximum of 78.8%. Finally, when a library ofPWMs representative of hundreds of TF DNA-bindingspecificities was added (SVM3), an additional gain inaccuracy was obtained, although it is clear that the five

PWMs and the corresponding DSs are themselves suffi-cient for an accurate prediction. The most predictivefeatures (namely, those binding sites that were morefrequently retrieved in 100 independent instances of thefeature selection) and their association with constitutiveor inducible peaks are shown in Figure 3D. Interestinglyat 4 h after LPS, only PWM1 (PU.1/IRF) and PWM5 (IRF/AP-1) were sufficient for maximal prediction accuracy.Instead, at 2 h, the multimerized IRF site had a strongimpact on prediction accuracy, suggesting that coopera-tive interactions with different TFs control inducibleIRF8 binding during the course of the LPS response.Importantly, the gain in accuracy obtained using theadditional 742 PWMs was almost exclusively due toPU.1 (Spi-like)-binding sites, which were relevant topredict constitutive IRF8 binding. Therefore, constitutiveIRF8 peaks were associated with composite PU.1/IRFsites and canonical PU.1 sites (since IRF8 recruitmentin this case is likely due to protein–protein contacts with

Figure 2. Relationship between basal and LPS-inducible IRF1 and IRF8 binding. (A) Number of IRF1 peaks before and after LPSstimulation (2 h and 4 h) (MACS P < 13 10�10). (B) Cumulative distribution of the distances between the summits of IRF1 and PU.1 peaksin untreated (UT) macrophages. (C) Venn diagrams show the overlap between IRF1 and IRF8 peaks in untreated and LPS-treatedmacrophages. (D) PWMs identified by de novomotif discovery at the indicated groups of IRF1 and IRF8 peaks (4 h after LPS stimulation). (E)A representative snapshot in which some differences between the genomic distributions of IRF1 and IRF8 were highlighted.

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PU.1 in the absence of direct DNA recognition), while theinducible ones were linked to multimerized IRF sites andIRF/AP-1 composite sites.

IRF8 binding to chromatin in Bxh2 macrophages

To determine the impact of IRF8 on the macrophageepigenome and gene expression programs, we took ad-vantage of the mutated (IRF8 R294C) Bxh2 cells. Indeed,the macrophage yield of Irf8�/� bone marrow cells is verylow (approximately one-fifth of wild-type cells), whichimplies the occurrence of some selection process during

the differentiation of progenitors into macrophages. Con-versely, the macrophage generation efficiency of Bxh2and wild-type bone marrow was indistinguishable, whichlikely reflects the preservation of a subset of IRF8-bindingevents in this mutant. The IRF8 protein amount wasslightly but reproducibly lower in Bxh2 macrophages andwas not increased in response to LPS stimulation (Supple-mental Fig. 2A). Consistently, IRF8 constitutively boundits own locus (Supplemental Fig. 2B), mainly at an up-stream enhancer whose LPS-induced acetylation wasgreatly reduced in Bxh2 macrophages. These data indicatethat IRF8 controls its own LPS-inducible expression.

Figure 3. A small number of IRF-like DNA-binding sites predict constitutive versus LPS-inducible IRF8 recruitment. (A) Outline ofthe computational procedure used to retrieve sites bound by IRF8 in a constitutive or LPS-inducible manner. A de novo motif discoveryapproach (MEME) first retrieved PWM1 and PWM2, which were converted into DSs (DS1 and DS2, respectively) to determine thefraction of peaks in the two groups with a perfect match. Reiteration of the de novo motif discovery on the peaks without matchretrieved PWM3–5 and the corresponding DSs. (B) Scheme of the SVM with feature selection used in this study. (C) The SVM was runusing a combination of three sets of DNA-binding sites of increasing complexity: only PWM1–5 (SVM1), PWM1–5 and DS1–6 (SVM2),and finally, PWM1–5+DS1–6 and a set of 742 PWMs corresponding to annotated high-quality TF DNA-binding specificities (SVM3). (D)The most predictive DNA-binding sites (namely, those most frequently retrieved in 100 iterations of the three SVMs) and theirassociation with either constitutive or LPS-inducible IRF8 peaks are shown.






Overall, IRF8 binding was abolished or greatly reducedgenome-wide in Bxh2 macrophages compared with theirwild-type counterpart (Fig. 4A,D, red dots), althougha relatively small population of peaks was not signifi-cantly affected by the mutation (Fig. 4A, gray peaks closeto the diagonal). This residual IRF8 binding may contrib-ute to explaining the milder phenotype of the Bxh2mutation relative to the complete loss of IRF8 and,specifically, themore efficient generation of macrophagesby Bxh2 mutant bone marrow cells.We next tested the effects of the global IRF8-binding

reduction on PU.1 genomic occupancy (Fig. 4B,E). Al-though the genomic distribution of PU.1 was mostlyunperturbed, 8.7% of PU.1 peaks (n = 6586) (Fig. 4B,E,red dots) were strongly reduced. At all time points, IRF8-dependent PU.1 peaks showed a strong overrepresenta-tion of the composite PU.1/IRF8 site (PWM1) whencompared with the PU.1 peaks that were unaffected(E-value = 1 3 10�5069 at the 4-h time point). We alsodetected PU.1 peaks that were increased in Bxh2 macro-phages, but enhanced binding was at an overall lowermagnitude and frequency than loss of binding, suggestingthat it may represent an indirect effect of the mutation.Finally, while global genomic histone acetylation (spe-

cifically, H3K27Ac) was unperturbed in Bxh2 macro-phages, it was strongly (albeit not uniformly) reduced atgenomic regions where IRF8 binding was abrogated orreduced in Bxh2 cells (Fig. 4C,F), which indicates thatIRF8 critically contributes to the maintenance of anactive chromatin state at a subset of cis-regulatoryelements of unstimulated macrophages. Scatter plots

obtained from LPS-stimulated macrophages showed verysimilar results (Supplemental Fig. 3).

Basal and inducible gene expression programsregulated by IRF8

RNA sequencing (RNA-seq) experiments in untreatedand LPS-treated Bxh2 macrophages showed two majortrends (Fig. 5A; Supplemental Table 4). First, a largecluster (#2) of 323 genes and two smaller clusters (#1and #3) that were down-regulated after LPS stimulationwere expressed at higher levels in unstimulated Bxh2macrophages relative to their wild-type counterpart.Clusters #1 and #2 were enriched for gene ontology(GO) terms related to cell cycle and mitosis. Increasedexpression of cell cycle and mitotic genes may contributeto the development of the chronic myelogenous leuke-mia-like syndrome caused by the IRF8 deficiency(Turcotte et al. 2005). The genomic regions surrounding(62.5 kb) the transcription start sites (TSSs) of these geneswere not enriched for IRF TF-binding sites, including thefive PWMs shown above (Fig. 5A). Up-regulation of thesegenes was therefore likely to be an indirect effect of theloss of IRF8 activity. Second, a large group of genes wasdown-regulated in Bxh2 macrophages, including consti-tutively expressed and noninducible genes (clusters #4and #5) (Fig. 5A) and LPS-inducible genes (cluster #6).Cluster #6 was enriched for GO terms related to IFNsignaling. Consistently, gene set enrichment analysis(GSEA) (Fig. 5B) detected a strong enrichment of anIFNb-stimulated gene (ISG) set in wild-type macro-

Figure 4. Impact of the Bxh2 mutation on IRF8,PU.1, and histone acetylation. Scatter plots indicatingIRF8 (A) and PU.1 (B) levels in Bxh2 macrophagesrelative to wild-type cells. (C) H3K27Ac sequencingtag counts in Bxh2 macrophages relative to wild-typemacrophages. The box plot on the left showsH3K27Ac data at all locations where H3K27Ac wasdetected in wild-type macrophages, while the one onthe right shows H3K27Ac tags at IRF8 peaks reducedin the Bxh2 mutant (P = 2.93 10�152 Wilcoxon ranksum test). The ChIP-seq snapshot on the right showsrepresentative behaviors of IRF8 (D), PU.1 (E), andH3K27Ac (F) at a selected genomic location.

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phages. In particular, of the 251 genes in cluster #6, 132(52.5%) were ISGs (based on either their inducibility bytype I IFNs or the requirement of the type I IFN receptorfor their activation in response to LPS) (Raza et al. 2010;Cheng et al. 2011). Seventy-eight of these 132 ISGs weredown-regulated also in untreated cells (Fig. 5A). Theremaining 119 genes included a heterogeneous group ofLPS-inducible genes whose promoters were enriched forEGR1–3-binding sites. Consistently, IRF8 was reported toactivate the expression of EGR family TFs (Kurotaki et al.2013), and expression of EGR1 and EGR3 was reduced inBxh2 macrophages (Supplemental Fig. 4). When the pro-moters of the ISGs in this cluster were compared withthose of non-ISGs, a very strong enrichment for IRFPWMs was detected (E-value = 2.01 3 10�34 for thecanonical ISRE).We next analyzed the presence of PWM1–5 in the

regions surrounding the TSSs (62.5 kb) of the geneswhose expression depends on IRF8 (clusters #4–#6).Cluster #6 (mainly LPS-inducible genes) showed a strongoverrepresentation of PWM1–3 (with PWM4 and PWM5

reaching a lower statistical significance) (Fig. 5A), whilecluster #5 (mainly constitutively expressed genes)showed a strong overrepresentation of only PWM1 andPWM4, corresponding to the PU.1/IRF8 PWM and anIRF/ETS composite site, respectively (Fig. 3), and bothpredictive of constitutive IRF8 binding in the SVM (Fig.3D). Lack of enrichment of any of the five PWMs incluster #4 suggests that down-regulation of these genes inBxh2 macrophages may represent an indirect effect ofIRF8 inactivation. This analysis indicates that induciblegenes and, specifically, ISGs were associated with bothconstitutive binding sites (which enable their premarkingby IRF8/PU.1) and inducible sites (which enable addi-tional IRF8 recruitment, possibly together with otherIRFs and AP-1 proteins, in response to stimulation). Lossof constitutive IRF8/PU.1 binding may contribute toreduced constitutive expression of many of the ISGs inunstimulated Bxh2 macrophages (Fig. 5A). Conversely,constitutively expressed and noninducible genes con-tained exclusively binding sites mediating constitutiveIRF8/PU.1 recruitment.

Figure 5. Impairment of the LPS response in Bxh2 macrophages. (A) Differentially expressed genes in wild-type versus Bxh2macrophages were identified by RNA-seq. Data in the heat map are expressed as log2 (fold change) and are hierarchically clustered. Thenumbers at the right of the heat map indicate the identified gene expression clusters. Clusters #1–3 are genes overexpressed in Bxh2macrophages, and clusters #4–6 are genes down-regulated in Bxh2 macrophages. The E-values associated with the five PWMs describedin Figure 3 (in a region including 62.5 kb from the TSS) are shown at the right. (B) An IFNb-regulated gene set was down-regulated inBxh2 macrophages. (C) Western blot analysis showing the effect of the Bxh2 mutation on STAT1, IRF3, IRF1, and ΙkBa activation byLPS. (D) RNA-seq and ChIP-seq snapshot at the Ifnb1 gene locus.






Defective induction of ISGs in Bxh2 macrophages maybe explained by the defective induction of the Ifnb1 genein Bxh2 macrophages (Supplemental Table 4), which is inkeepingwith the data reported in dendritic cells (Schiavoniet al. 2002; Tsujimura et al. 2003). Reduced productionof IFNb was also indirectly confirmed by the reducedphosphorylation of STAT1 and reduced induction of IRF1in response to LPS stimulation (Fig. 5C).Visual inspection of the ChIP-seq data (Fig. 5D) con-

firmed that the Ifnb1 gene promoter was constitutivelybound by IRF8 and that PU.1 association with it waslargely IRF8 dependent. Binding of IRF8 and PU.1 to theIFNb promoter in human and mouse monocytes waspreviously mapped to promoter sites resembling PWM1(a composite ETS/IRF site that differs from PWM1because of a 4-nt spacer between the 59-GGAA-39 ETSconsensus and the 59-GAAA-39 IRF consensus) andPWM4 (Li et al. 2011) and is fully consistent with ourChIP-seq data. Moreover, constitutive IRF8/PU.1 bindingwas shown to be required for IRF3 recruitment, thusexplaining reduced IFNb induction in cells depleted ofIRF8 (Li et al. 2011). Macrophages and many other cellsare also known to constitutively produce extremely lowlevels of IFNb (close or below the detection limit) thatare, however, important to maintain the basal expressionof some genes relevant for the subsequent response toboth type I and type II IFNs; notably STAT1 and itsbinding partner, IRF9 (Ivashkiv and Donlin 2014). At leastin fibroblasts, basal expression of IFNb was attributed toJUN/AP-1-mediated regulation (Gough et al. 2010), but,in vivo, it may result from more complex regulatorycircuits, such as the tonic macrophage stimulation by themicrobiome (Ivashkiv and Donlin 2014). However, whileIRF8 was clearly essential for maximal production ofIFNb in response to LPS, we have no clear evidence of itspossible role in maintaining basal IFNb expression, sinceSTAT1 levels in unstimulated conditions were similar inwild-type and Bxh2 macrophages (Fig. 5C), and its geno-mic recruitment in response to IFNb and IFNg stimula-tion was largely unaffected (see below). Therefore, wefavor the hypothesis that reduced basal expression ofmany ISGs in unstimulated Bxh2 cells was not due toreduced basal IFNb secretion but mainly lack of consti-tutive binding of their promoters and regulatory elementsby IRF8/PU.1.In contrast to STAT1, the activation of IRF3, which is

mediated by protein kinases directly activated upon LPSstimulation and is required to induce Ifnb1 gene tran-scription, was unaffected in the Bxh2 mutant (as assessedby normal levels of IRF3 phosphorylation) (Fig. 5C).Similarly, activation of the NF-kB pathway, as measuredby degradation and NF-kB-dependent resynthesis of IkBa,was identical in wild-type and Bxh2 macrophages.Finally, since the GREAT analysis shown in Figure 1E

demonstrated a strong association of constitutive IRF8peaks with several ontology terms related to purinergicreceptor signaling, we analyzed the impact of the Bxh2mutation on these genes. Strikingly, nine purinergicreceptor genes belonging to different subgroups withdistinct nucleotide recognition specificity (e.g., Adora3,

P2rx4, and P2ry12) were significantly down-regulated inBxh2 macrophages—in most cases, both before and afterLPS treatment (Supplemental Table 5). These genes wereusually constitutively bound by IRF8 and PU.1 at eithertheir promoter or cis-regulatory regions nearby (Supple-mental Table 5), thus suggesting that IRF8 directlycontrols the responsiveness of macrophages to a largenumber of nucleotide species. IRF8 also directly con-trolled the expression of Entpd1, which encodes the onlyectonucleotidase (CD39) catalyzing the hydrolysis of ATPand ADP at the macrophage surface (Levesque et al.2010), implicating IRF8 in the regulation of ATP signalingand metabolism.

IRF8 controls the IFN response downstream from Ifnb1gene induction

The predominant transcriptional outcomes in LPS-stim-ulated Bxh2 macrophages were an impairment of theinterferon response and a reduced expression of non-ISGslikely regulated by EGR family TFs (Kurotaki et al. 2013).We set out to obtain additional mechanistic insight intothe role of IRF8 in the control of IFNb-regulated geneexpression and epigenomic changes. Specifically, weasked whether IRF8 is exclusively required for Ifnb1 geneactivation or instead collaborates with IFNb-activatedSTATs in the induction of IFNb-activated genes (Ivashkivand Donlin 2014). According to current models, IFNa/bbinding to their receptor (IFNAR) mainly promotes therelease of STAT1/STAT2/IRF9 trimers that preferentiallybind IRF-like sites (ISREs) because their binding specific-ity is determined by the IRF9 subunit. Conversely, IFNgactivates STAT1 homodimers that preferentially bindGAS (g-activated sites) sequences (Ivashkiv and Donlin2014). To address this question, we first generated STAT1and STAT2 ChIP-seq data in macrophages stimulatedwith LPS and evaluated whether STAT1 and STAT2landing sites in the genome were prebound by IRF8.STAT1/STAT2/IRF9 activation in this context is depen-dent on IRF3-mediated activation of the Ifnb1 gene(Doyle et al. 2002) and the subsequent autocrine andparacrine activities of newly synthesized IFNb (Thomaset al. 2006). Overall, the overlap between STAT1 andSTAT2 ChIP-seq data sets was very high (Fig. 6A), thusindirectly confirming that the main STAT1 species re-leased upon LPS stimulation is the canonical STAT1/STAT2/IRF9 trimer binding IRF-like sites (Fig. 6A). Nev-ertheless, a substantial fraction of STAT1 peaks did notoverlap STAT2 peaks and showed a clear preferencetoward GAS-like sites (Fig. 6A). Based on their relation-ship with IRF8, we identified three distinct groups ofgenomic regions contacted by STAT1/STAT2 in an LPS-inducible manner (Fig. 6B); namely, regions associatedwith constitutive (n = 707) or inducible (n = 1301) IRF8and regions negative for IRF8 (or with low IRF8 levels thatwere below the threshold selected for peak calling; n =1158). Overall, about two-thirds of the genomic regionsbound by STAT1 in response to LPS were also associatedwith IRF8 (in either a constitutive or an induciblemanner).

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The heat map in Figure 6B also shows that the behaviorof PU.1 at these regions paralleled that of IRF8. In fact,regulatory elements constitutively associated with IRF8were also constitutively bound by PU.1 (Fig. 6B, blue bar,left); regions with inducible IRF8 showed low basal PU.1binding that was increased in response to stimulation(Fig. 6B, orange bar, middle), and STAT1/STAT2-boundregions with no IRF8 binding were, in general, character-ized by comparatively low PU.1 signals that were notsignificantly (or only slightly) affected by stimulation.A motif discovery analysis on STAT1 peaks that over-

lapped and peaks that did not overlap IRF8 identifiedagain two distinct types of DNA-binding sites (Fig. 6C).IRF8-associated STAT1 peaks were mainly associatedwith ISRE-like sites, while IRF8-negative STAT1 peakswere strongly enriched for a GAS-like site (Jolma et al.2013; Ivashkiv and Donlin 2014), thus suggesting that theSTAT1 species contacting these sites may be STAT1homodimers like those released upon IFNg stimulation.A representative snapshot in Figure 6D shows a genomic

region containing multiple STAT1 and STAT2 peaksassociated with either constitutive or inducible IRF8peaks.Overall, the IRF8 requirement for the induction of the

Ifnb1 gene and even more so the extensive overlapbetween the genomic distribution of IFNb-activatedSTAT1/STAT2 and IRF8 indicate a close functional re-lationship between themain IFNb-activated TF and IRF8.

IRF8 synergizes with STAT1 in the inductionof IFNb-activated genes

Because of the extensive overlap of LPS-induced STAT1peaks and IRF8, we asked whether and to what extentIRF8 collaborates with STAT1 in the induction of IFNb-activated genes. To address this question, we could notuse LPS stimulation of Bxh2macrophages, since the IFNb

response was greatly impaired in these cells (Fig. 5).Therefore we stimulated macrophages with recombinantIFNb and tested the impact of the Bxh2 mutation on gene

Figure 6. Correlation between STAT1/STAT2 and IRF8 genomic occupancy in LPS-treated macrophages. (A) Overlap betweeninducible STAT1 and STAT2 ChIP-seq peaks at 2 h after LPS stimulation. The PWMs at the right were retrieved by de novo motifdiscovery on either STAT1/STAT2 overlapping peaks (top panel) or STAT1 peaks that did not overlap STAT2 (bottom panel). (B) STAT1and STAT2 genomic distributions in LPS-activated macrophages. In the heat map, IRF8 ChIP-seq data for the same genomic regionswhere STAT1 binding was detected are shown. Data were ordered on the basis of the presence or absence of IRF8 signals and thebehavior (constitutive or inducible) of IRF8 peaks. STAT2 binding to the same regions is shown. (C) PWMs overrepresented in LPS-activated STAT1 peaks that either overlap or do not overlap with IRF8. (D) ChIP-seq snapshot showing the recruitment of STAT1,STAT2, and IRF8 to a representative genomic region containing the LPS-inducible and IFNb-dependent genes Rsad2 and Cmpk2.






expression, STAT1 binding, and histone acetylation ofactivated macrophages.The response of Bxh2 macrophages to IFNb stimula-

tion was almost indistinguishable from that of their wild-type counterpart, as indicated by STAT1 phosphorylationover a 4-h time course (Supplemental Fig. 5A). Impor-tantly, IFNb induced IRF8 protein expression (Supple-mental Fig. 5A). This effect was correlated with a prom-inent binding of STAT1 to both the Irf8 gene promoterand an upstream enhancer (Supplemental Fig. 5B) and theinduction of the Irf8 mRNA (approximately twofold atthe time points used for RNA-seq). Neither STAT1binding nor increased Irf8 mRNA after IFNb stimulationwas reduced in Bxh2macrophages (in fact, they were bothslightly augmented). Therefore, while the up-regulationof IRF8 in response to LPS was impaired in Bxh2 macro-phages, its induction by IFNb was unaffected.Since the peak of STAT1 phosphorylation in response

to IFNb occurred at 30 min and strongly declined after 60min (Supplemental Fig. 5A), we focused our initialanalysis on the first hour after stimulation. Of the 656genes induced in response to IFNb stimulation in thistime window, 148 (22.6%) showed reduced activation inBxh2 macrophages (Fig. 7A; Supplemental Table 6). Asdiscussed above, the transcripts of many IRF8-dependentIFNb-inducible genes were less abundant already beforestimulation (heat map in Fig. 7A), suggesting a role forIRF8 in maintaining their basal level of activity. Genesdown-regulated in Bxh2 macrophages included canonicalIFNb response genes directly bound and activated bySTAT1, such as Mx1 and Mx2, whose induction wasalmost completely abrogated in IRF8 mutant cells (Fig.7B). Conversely, only a small group of 33 IFNb-activatedgenes (5%) showed a mild increase in expression in IFNb-stimulated Bxh2 macrophages, which may relate to thepreviously described activity of IRF8 as a negative regulatorof interferon-stimulated genes (Rosenbauer et al. 1999).The complexity of the effects of the Bxh2 mutation on

STAT1 binding is exemplified by its behavior at theMx1–Mx2 locus (Fig. 7B). While STAT1 binding to the Mx2promoter was virtually unaffected, its recruitment to theMx1 promoter was almost completely abrogated in Bxh2macrophages. Both promoters, however, were constitu-tively bound by IRF8, whose occupancy dropped in Bxh2cells. The possibility that the residual IRF8 and PU.1binding observed in Bxh2 macrophages at the Mx2 genepromoter may suffice to enable STAT1 recruitmentshould not be discounted. However, in spite of thedifferent effects on STAT1 recruitment, the induction ofboth genes was strongly reduced or nearly completelyabrogated in Bxh2 cells.Genome-wide, of the 13,261 STAT1 peaks observed at

30 min after IFNb stimulation, 38.4% (5094) overlappedwith IRF8 peaks. However, only 326 peaks were signifi-cantly reduced in Bxh2macrophages. Therefore, althoughthe recruitment of STAT1 at some typical IFNb-activatedgenes (such as Mx1) required IRF8, the overall genomicSTAT1 landscape was only marginally perturbed. Whilethe invariant STAT1 peaks were enriched (E-value = 4.1310�793) for a GAS-like site similar to the one shown in

Figure 6C, the peaks reduced in Bxh2 cells were enrichedfor the canonical composite PU.1–IRF8 site (E-value =4.3 3 10�394). We also analyzed the impact of IRF8 onSTAT1 recruitment using a more extended kinetics of IFNbstimulation (up to 4 h). Overall, also at later time points,most STAT1-binding events were not significantly af-fected by the IRF8 mutation: Two-hundred-eighty-eightSTAT1 peaks were significantly reduced at 2 h, and only60 were significantly reduced at 4 h after IFNb stimula-tion. A representative snapshot is shown in SupplementalFigure 6.We next analyzed histone acetylation after IFNb stim-

ulation at genomic regions associated with IRF8 occu-pancy (Fig. 7C). While 13,128 acetylated regions at 30minpost-stimulation (15,040 at 60min) were not significantlyaffected by the Bxh2mutation, 896 regions at 30min (980at 60 min) were strongly down-regulated, a result that isconsistent with the effects of the Irf8 mutation on IFNb-induced gene expression. STAT1 binding at regions whoseacetylation was unaffected did not display clear andsignificant differences in wild-type and Bxh2 macro-phages. Conversely, median STAT1 binding was stronglyreduced at regions whose acetylation was lower in Bxh2macrophages (2.2-fold; P = 4.9 3 10�54, Wilcoxon ranksum test) (Fig. 7C). Therefore, STAT1 recruitment wascritically reduced at those regions whose activation(measured by inducible histone acetylation) was impairedin IRF8 mutant cells even though the overall genomicSTAT1-binding landscape was onlyminimally affected bythe IRF8 mutation.Finally, we tested the effects of the Bxh2 mutation on

IFNg-induced STAT1 binding that, as discussed above, ismainly mediated by GASs. IFNg treatment induced 5993STAT1 peaks at 1 h and 1293 peaks at 2 h. However, only211 STAT1 peaks were reduced in the Bxh2 macrophagesat 1 h and three peaks were reduced at 2 h post-stimulation (Supplemental Fig. 7). Overall, IRF8 had verymarginal effects on recruitment of STAT1 homodimersafter IFNg stimulation.

Discussion

The objective of this study was to understand at a genomescale themechanistic basis for the involvement of the sameTF in both developmental and inducible gene expressionprograms. IRF8 represents a paradigmatic example, since itis required for terminal macrophage differentiation and, atthe same time, is necessary for the activation of somecrucial inflammatory genes, notably Ifnb1.The analysis of the IRF8 genomic distribution before

and after LPS stimulation allowed us to identify twodistinct sets of binding events together with the cis-regulatory code explaining them. Rather unusually fora TF involved in developmental decisions, IRF8 dis-played a genomic distribution with two clearly distin-guishable components; namely, a constitutive compo-nent associated with composite PU.1/IRF8 sites orcanonical PU.1 sites and therefore with high-level con-stitutive occupancy by PU.1 and an inducible compo-nent that was stimulus-dependent and relied on the

Mancino et al.





existence of a completely different set of binding sites,including multimerized IRF sites and IRF/AP-1 compos-ite sites. Probably because of both their low affinity andthe requirement for additional binding partners (namely,other IRF or AP-1 family TFs), such sites were unable tobind IRF8 in basal conditions. When the expression andprotein amount of IRF8 were increased because of IFNbrelease and autocrine activity (Ivashkiv and Donlin2014) together with increased expression of other IRFs(notably IRF1) and AP-1 proteins, IRF8 became able tocontact these IRF sites, a phenomenon that closelyresembles the recently described activation-inducibleIRF4 recruitment in B lymphocytes (Ochiai et al. 2013).In turn, these sites appear to be relevant for the imple-mentation of the IFNb response by STAT1, sincea sizeable fraction of the interferon-regulated genesrequired IRF8 for maximal induction. Since IRF8 is itselfrequired for IFNb induction in response to LPS, thisregulatory circuit configures a feed-forward loop with

a self-reinforcement component by which STAT1 con-trols the increased Irf8 transcription.In addition to the Ifnb1 gene, the constitutive compo-

nent of the IRF8 genomic distribution was associatedwith the regulation of a number of genes critical for notonly basal macrophage functions but also the response tostimulation, including complement factors, pattern rec-ognition receptors (such as TLR9, whose expression wasalmost completely abolished in Bxh2 macrophages), andseveral purinergic receptors. The association of IRF8 withgenes encoding purinergic receptors was particularlystriking in more than one respect. On the one hand,many of the highest-affinity IRF8 sites detected in themacrophage genome occurred at loci containing puriner-gic receptor genes, to the point that the most enrichedGO terms identified as associated with basal IRF8-bind-ing events were all related to purinergic receptor signal-ing. On the other hand, about half of the genes encodingpurinergic receptors as well as the only macrophage

Figure 7. IRF8 requirement for binding of and transactivation by STAT1 in IFNb-stimulated macrophages. (A) Heat map showingRNA-seq data in wild-type and Bxh2 macrophages stimulated with IFNb as indicated. Genes were divided in three groups based ontheir behavior in Bxh2 relative to wild-type macrophages. (B) Genomic snapshot of the Mx1–Mx2 locus showing IFNb-induced STAT1peaks affected or not affected in Bxh2 macrophages. (C) Box plot showing H3K27Ac, STAT1, and IRF8 tag densities at genomic regionsshowing reduced (top box plot) or unaffected (bottom box plot) H3K27Ac in Bxh2 versus wild-type macrophages.






ectonucleotidase (CD39) that degrades extracellular ATPand ADP were affected by the loss of IRF8 function.Therefore, a major critical role of IRF8 in macrophages isto regulate all of those functions (including, but not only,macrophage chemotaxis and IL1b secretion) that aredirectly controlled by purines (Kronlage et al. 2010;Ulmann et al. 2010; Bours et al. 2011). Previous data inIrf8�/� monocyte–dendritic cell progenitors (MDPs) sug-gested a role for IRF8 in controlling the expression ofKlf4,an additional TF required for macrophage development,as well as some EGR family TFs, which are rapidlyinduced in response to many stimuli, including LPS(Kurotaki et al. 2013). In terminally differentiated mac-rophages such as those used in our study, the expressionof Klf4 was substantially identical in Bxh2 and wild-typemacrophages (data not shown). This discrepancy may bedue to the residual IRF8 activity in Bxh2 cells, whichmayalso explain their higher ability to differentiate intomacrophages as compared with Irf8�/� bone marrowcells. Alternatively, the defect in Klf4 expression ob-served in Irf8�/� MDPs may reflect a transient impair-ment that is overcome when differentiation progresses.Conversely, the expression of EGR1 and EGR3 was sub-stantially reduced in Bxh2 macrophages. Consistent withthis observation, almost half of the LPS-inducible genesthat were down-regulated in Bxh2 macrophages were notISGs, and their promoters were enriched in EGR TF-binding sites.This study also revealed an unexpected complexity in

the interplay between two master regulators of macro-phage development; namely, PU.1 and IRF8. PU.1 hasa very broad role in controlling the macrophage cis-regulatory repertoire (Ghisletti et al. 2010; Heinz et al.2010), since it is also pervasively required to maintainnucleosome depletion (and therefore the accessibility ofthe underlying regulatory information) at macrophageenhancers (Barozzi et al. 2014). Many TFs that areactivated or induced in response to extracellular stimuli(including inflammatory agonists) were shown to bindregions that were premarked andmade accessible by PU.1(Ghisletti et al. 2010), and PU.1 binding was, in fact,necessary for their recruitment (Escoubet-Lozach et al.2011; Heinz et al. 2013). The inability of TFs such as NF-kB to contact sites embedded in a nucleosomal context(Natoli 2009; Lone et al. 2013) provides a mechanisticbasis for these observations. The general model suggestedby these studies is that the regulatory landscape createdby lineage-determining TFs determines and, in fact,limits the activity of stimulus-inducible TFs by definingthe fraction of the genomic regulatory repertoire that isavailable for them to bind (Natoli 2010). This model is inkeeping with the well-established notion that the en-hancer repertoire of distinct cells types is very specific, isdistinct from that of other cells, and exists before stim-ulation (Heintzman et al. 2009). The discovery of regula-tory elements (latent or de novo enhancers) (Kaikkonenet al. 2013; Ostuni et al. 2013) that are not associated witheither histone marks or constitutively bound TFs andwhose emergence from latency requires activation withspecific stimuli explains why the exposure to environ-

mental changes has a direct impact on the regulatoryinformation made available for gene regulation (Gosselinet al. 2014; Lavin et al. 2014). IRF8 directly contributes tothe appearance of latent enhancers, since about one-thirdof the latent enhancers induced by a 4-h LPS stimulationcoincided with LPS-induced IRF8 peaks associated withPWMs enabling inducible IRF8 recruitment. In general,many of the novel and LPS-inducible IRF8-binding eventsoccurred at genomic regions that were not premarked byPU.1 in unstimulated macrophages and were at a consid-erable distance from constitutively PU.1-bound regions.Therefore, IRF8 may represent one of those few TFs thatcan directly invade chromatinized and originally inacces-sible, not premarked, sites and get them involved in generegulation.

Materials and methods

Mice

Animal experiments were performed in accordance with theItalian laws (D.L.vo 116/92 and following additions), whichenforce the EU 86/609 directive. The Bxh2/TyJ mouse strainwas obtained from the Jackson Laboratory in a C3H/HeJ back-ground that is resistant to LPS stimulation due to a mutation inTLR4 (Tlr4Lps-d). BXH2/TyJ males were therefore crossed withC57BL/6 females to generate F1 mice that were then inter-crossed to produce an F2 progeny. F2 littermates were crossed togenerate mice not carrying Tlr4Lps-d and either homozygous forIRF8R294C (BXH2 mice) or wild type for IRF8. TaqMan probeswere designed to perform SNP analysis of mouse tail DNA; inparticular, 59-CTACACCATGAATAAA-39 for Tlr4Lps-d, 59-CTACACCAGGAATAAA -39 for Tlr4wt, 59-AACACGCAGCCCTG-39 for IRF8R294C, and 59-AACACGCGGCCCTG-39 for IRF8wt.

Cell culture

Macrophage cultures were carried out as described (Austenaaet al. 2012). LPS from Escherichia coli serotype EH100 (Alexis)was used at 10 ng/mL. Mouse recombinant IFNb (Millipore, no.IF011) and IFNg (R&D Systems, no. 485-MI) were used ata concentration of 100 U/mL.

Antibodies

An anti-IRF8 rabbit polyclonal antibody was raised in-house andaffinity-purified. The anti-Pu.1 antibody has been previouslydescribed (Ostuni et al. 2013). The following antibodies werealso used: phospho-STAT1 (Tyr701; Cell Signaling Technology,no. 9171), STAT1 (Cell Signaling Technology, no. 9172), IkBa(Santa Cruz Biotechnology, sc-371), phospho-IRF3 (Cell Signal-ing Technology, no. 4947), IRF3 (Cell Signaling Technology, no.4302), IRF1 (sc-640), and tubulin (Sigma, T9026). For quantifiedimages, secondary IRDye antibodies from Li-Cor were used(catalog nos. 926-68021 and 926-32210).

ChIP-seq and RNA-seq

Fixed macrophages (5 3 106 to 15 3 106 [ChIP-seq for H3K27Acand Pu.1], 30 3 106 [STAT2 and IRF1], or 100 3 106 [IRF8 andSTAT1]) were lysed with RIPA buffer and, after chromatinshearing by sonication, incubated overnight at 4°C with proteinG Dynabeads (Invitrogen) that were previously coupled with 3–10 mg of antibody (Ghisletti et al. 2010; Austenaa et al. 2012).

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Antibodies used for ChIP-seq included STAT1 (sc-592),STAT2 (sc-950), IRF1 (sc-640), H3K27Ac (Abcam, ab4729),homemade PU.1, and IRF8 antibodies. DNA yield was ;200ng per 107 cells for H3K27Ac, 20 ng per 107 cells for PU1, and1 ng per 107 cells for IRF1, IRF8, STAT1, and STAT2. Librarypreparation for Illumina sequencing was carried out using a pre-viously described protocol (Garber et al. 2012) with slight modifi-cations (Ostuni et al. 2013). Total RNAwas extracted from 53 106

cells using RNAeasy kit (Qiagen), and libraries were prepared afteroligo-dT selection using the TruSeq RNA sample preparation kit(Illumina).

Computational methods

Short reads obtained from Illumina HiSeq 2000 runs werequality-filtered according to the Illumina pipeline. Analysis ofthe data sets was automated using the ‘‘Fish the ChIPs’’ pipeline(Barozzi et al. 2011).

For RNA-seq, after quality filtering according to the Illuminapipeline, 51-base-pair (bp) paired-end reads were aligned to themm9 reference genome and the Mus musculus transcriptome(Ensembl build 63) (Flicek et al. 2012) using TopHat (Trapnellet al. 2012). Transcript abundance was quantified, and differen-tially expressed genes were called using Cufflinks 1.2.1 (Trapnellet al. 2012). Detailed computational methods are described in theSupplemental Material.

The SVM approach has been recently described (Barozzi et al.2014). In this specific case, we split the original data sets intoa training set and a test set of identical size.

Accession numbers

Raw data sets are available for download at the Gene ExpressionOmnibus (GEO) database (http://www.ncbi.nlm.nih.gov/gds) un-der the accession number GSE56123.

Acknowledgments

We thank Ido Amit, Philippe Gros, and Silvia Monticelli forcritically reading the manuscript. This work was supported bythe European Research Council (ERC grant NORM to G.N.).A.M. generated most data sets and the additional experimentaldata with contributions by S.G., R.O., and E.P.; A.T. computa-tionally analyzed all data sets; I.B. made the SVM analysis; K.O.provided critical reagents; and G.N. designed and supervised thestudy and wrote the manuscript with input from all coauthors.A.M. and A.T. contributed equally to this work and are listed inalphabetical order.

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